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All Journal Asian Journal of Science, Technology, Engineering, and Art Mikailalsys Journal of Mathematics and Statistics
Adamu M. M.
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Arts Computer Science & IT Engineering Mathematics Mechanical Engineering Social Sciences

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Two Strains of Covid-19 Model with Vaccination and the Effect of Awareness Program on Its Control Anate A. O.; Adamu M. M.; Adamu M.S.; Kwami A. M.
Asian Journal of Science, Technology, Engineering, and Art Vol 4 No 3 (2026): Asian Journal of Science, Technology, Engineering, and Art
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ajstea.v4i3.9383

Abstract

The Covid-19 outbreak and the subsequent emergence of different viral strains posed a serious global public health challenge. This study proposes a mathematical model to analyze the transmission dynamics of two different Covid-19 strains and examine the effect of awareness on disease control. The study established the basic mathematical properties of the model, analyzed the disease-free and disease-endemic equilibria for both strains, conducted stability analysis, and computed the basic reproduction number, defined as R₀ = max(R₁, R₂). Stability conditions were examined for the strain-specific reproduction numbers, including cases in which R₁ < 1 while R₂ > 1 and R₂ < 1 while R₁ > 1. Numerical simulations were also conducted to support the analytical results and further illustrate the model dynamics. The findings show that increased awareness enhances vaccination uptake and reduces the basic reproduction number, thereby contributing to the control of disease transmission. The study concludes that awareness-based interventions play an important role in controlling the spread of Covid-19 strains through improved vaccination behavior and reduced transmission potential. These findings contribute to mathematical epidemiology by demonstrating the relevance of awareness-driven vaccination strategies in multi-strain infectious disease models and provide practical implications for public health authorities in strengthening awareness campaigns through media and social gatherings.
Sensitivity Analysis of the Basic Reproduction Number for Two Strains Covid-19 Model with Vaccination and Awareness Program Anate A.O.; Adamu M. M.; Adamu M.S.; Kwami A. M.
Mikailalsys Journal of Mathematics and Statistics Vol 4 No 3 (2026): Mikailalsys Journal of Mathematics and Statistics
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjms.v4i3.9382

Abstract

Sensitivity analysis of the basic reproduction number is an essential mathematical tool for identifying the parameters that most strongly influence disease transmission in epidemiological models. This study analyzes the sensitivity of the basic reproduction number in a COVID-19 transmission model comprising seven mutually exclusive compartments and incorporating vaccination and awareness interventions. The basic reproduction number, R₀, was derived using the next-generation matrix method, after which local sensitivity analysis was conducted using data obtained from the Nigeria Centre for Disease Control and other sources. The analysis produced two values of R₀ whose magnitudes depend on the model parameters, particularly those associated with vaccination and public awareness. The findings indicate that recruitment and infection rates exert strong positive effects on disease transmission, whereas vaccination and natural recovery rates have negative effects on disease progression. These results demonstrate that reducing infection-related parameters while strengthening vaccination and recovery mechanisms is critical for controlling COVID-19 transmission. The study contributes to epidemiological modeling by identifying the parameters that should be prioritized in disease-control strategies. Accordingly, policymakers should implement coordinated interventions, including quarantine, lockdown measures, vaccination programs, and effective public awareness campaigns, to reduce transmission and limit disease growth.
Co-Authors Adamu M.S. Anate A. O. Anate A.O. Kwami A. M.